code: def _hydra_subprocess_cmd(
      local_rank: int,
  ) -> Tuple[Sequence[str], str]:
      from hydra.core.hydra_config import HydraConfig
      from hydra.utils import get_original_cwd, to_absolute_path
  
      import __main__  # local import to avoid https://github.com/Lightning-AI/lightning/issues/15218
  
      # when user is using hydra find the absolute path
      if __main__.__spec__ is None:  # pragma: no-cover
          command = [sys.executable, to_absolute_path(sys.argv[0])]
      else:
          command = [sys.executable, "-m", __main__.__spec__.name]
  
      command += sys.argv[1:]
  
      cwd = get_original_cwd()
      rundir = f'"{HydraConfig.get().run.dir}"'
      # Set output_subdir null since we don't want different subprocesses trying to write to config.yaml
      command += [
          f"hydra.run.dir={rundir}",
          f"hydra.job.name=train_ddp_process_{local_rank}",
          "hydra.output_subdir=null",
      ]
      return command, cwd
  
imports: import logging
  import os
  import signal
  import subprocess
  import sys
  import threading
  import time
  from typing import Any, Callable, List, Optional, Sequence, Tuple
  from lightning_utilities.core.imports import RequirementCache
  from typing_extensions import override
  from lightning.fabric.plugins.environments.cluster_environment import ClusterEnvironment
  from lightning.fabric.strategies.launchers.launcher import _Launcher
  from lightning.fabric.utilities.distributed import _set_num_threads_if_needed
  from lightning.fabric.utilities.rank_zero import rank_prefixed_message
label_desc: Use image node_id 2 for calling a global function with example usage: _hydra_subprocess_cmd(local_rank) and returns: command,  cwd